ZigZag - Deep Learning Hardware Design Space Exploration
This repository presents the novel version of our tried-and-tested hardware Architecture-Mapping Design Space Exploration (DSE) Framework for Deep Learning (DL) accelerators. ZigZag bridges the gap between algorithmic DL decisions and their acceleration cost on specialized accelerators through a fast and accurate hardware cost estimation.
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This is the complete list of members for LayerOperand, including all inherited members.
__eq__(self, "OperandABC" other) | OperandABC | |
__ge__(self, "OperandABC" other) | OperandABC | |
__hash__(self) | OperandABC | |
__init__(self, str name) | OperandABC | |
__jsonrepr__(self) | OperandABC | |
__lt__(self, "OperandABC" other) | OperandABC | |
__repr__(self) | OperandABC | |
__str__(self) | OperandABC | |
is_final_output(self) | LayerOperand | |
is_output(self) | LayerOperand | |
name(self) | OperandABC |